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A2009
Beginner
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FFT-Based 3D Convolution With Zero Padding

I have been trying to figure out how I can use Intel MKL to perform a FFT-based 3D convolution with zero-padding.  I have been searching and posting in online forums (including Intel MKL forum), unfortunately, I have not been very successful so far. 

I have a 3D array and is stored as a 1D array of type double in a columnwise fashion. Similarly the kernel is of type double and is saved columnwise. For example,

for( int k = 0; k < nk; k++ ) // Loop through the height.
    for( int j = 0; j < nj; j++ ) // Loop through the rows.
        for( int i = 0; i < ni; i++ ) // Loop through the columns.
        {
            ijk = i + ni * j + ni * nj * k;
            my3Darray[ ijk ] = 1.0;
        }

I am writing a 3D convolution function:

  • which takes in real values (not complex values) and
  • outputs the results of the convolution,
  • for the computation of convolution, I am performing a "not-in-place" FFT on the input array as well as the kernel in order to prevent them from getting modified (I need to use them later in my code) and
  • then do the backward computation "in-place".

During the process I am also considering the zero padding to avoid any artifacts.  The size of FFTs are (dim_input+dim_kernel-1) on each dimension and the next highest power of two is chosen for speed.

My questions are:

  1. How can I perform the zero-padding?
  2. How should I deal with the size of the arrays used by FFT functions?
  3. How can I take out the zero padded results and get the actual result?

I would be  absolutely grateful to have any comments or suggestion.

#include "mkl.h"

int max(int a, int b, int c);
void Conv3D_R2C( 
    double *in, int nRowsIn , int nColsIn , int nHeightsIn ,
    double *ker, int nRowsKer, int nColsKer, int nHeightsKer,
    double *out );
    
int main()
{

    int n = 5;
    int nkernel = 3;

    double *a          = new double [n*n*n]; // This array is real.
    double *aconvolved = new double [n*n*n]; // The convolved array is also real.
    double *kernel     = new double [nkernel*nkernel*nkernel]; // kernel is real.

    // Fill the array with some 'real' numbers.
    for( int i = 0; i < n*n*n; i++ )
        a[ i ] = 1.0;

    // Fill the kernel with some 'real' numbers.
    for( int i = 0; i < nkernel*nkernel*nkernel; i++ )
        kernel[ i ] = 1.0;

    // Calculate the convolution.
    Conv3D_R2C( a, n, n, n, kernel, nkernel, nkernel, nkernel, aconvolved );

    delete[] a;
    delete[] kernel;
    delete[] aconvolved;
}

void Conv3D_R2C( // Real to Complex 3D FFT.
    double *in, int nRowsIn , int nColsIn , int nHeightsIn ,
    double *ker, int nRowsKer, int nColsKer, int nHeightsKer,
    double *out )
{
    
    int nIn  = max( nRowsIn , nColsIn , nHeightsIn  );
    int nKer = max( nRowsKer, nColsKer, nHeightsKer );
    int n = nIn + nKer - 1;

    /* Strides describe data layout in real and conjugate-even domain. */
    MKL_LONG rs[4], cs[4];
    
    // DFTI descriptor.
    DFTI_DESCRIPTOR_HANDLE fft_desc = 0;
    
    // Round up to the next highest power of 2.
    unsigned int N = (unsigned int) n; // compute the next highest power of 2 of 32-bit n.
    N--;
    N |= N >> 1;
    N |= N >> 2;
    N |= N >> 4;
    N |= N >> 8;
    N |= N >> 16;
    N++;
    
    // Variables needed for out-of-place computations.
    MKL_Complex16 *in_fft  = new MKL_Complex16 [ N*N*N ];
    MKL_Complex16 *ker_fft = new MKL_Complex16 [ N*N*N ];
    MKL_Complex16 *out_fft = new MKL_Complex16 [ N*N*N ];
    double *out2 = new double [ N*N*N ];
   
    /* Compute strides */
    rs[3] = 1;           cs[3] = 1;
    rs[2] = (N/2+1)*2;   cs[2] = (N/2+1);
    rs[1] = N*(N/2+1)*2; cs[1] = N*(N/2+1);
    rs[0] = 0;           cs[0] = 0;
    
    // Create DFTI descriptor.
    MKL_LONG sizes[] = { N, N, N };
    DftiCreateDescriptor( &fft_desc, DFTI_DOUBLE, DFTI_REAL, 3, sizes );
    
    // Configure DFTI descriptor.
    DftiSetValue        ( fft_desc, DFTI_CONJUGATE_EVEN_STORAGE, DFTI_COMPLEX_COMPLEX );
    DftiSetValue        ( fft_desc, DFTI_PLACEMENT             , DFTI_NOT_INPLACE     ); // Out-of-place transformation.
    DftiSetValue        ( fft_desc, DFTI_INPUT_STRIDES  , rs  );
    DftiSetValue        ( fft_desc, DFTI_OUTPUT_STRIDES , cs  );
    DftiCommitDescriptor( fft_desc );
    DftiComputeForward  ( fft_desc, in , in_fft  );
    DftiComputeForward  ( fft_desc, ker, ker_fft );

    for(long long i = 0; i < (long long)N*N*N; i++ )
    {
        out_fft.real = in_fft.real * ker_fft.real;
        out_fft.imag = in_fft.imag * ker_fft.imag;
    }

    // Change strides to compute backward transform.
    DftiSetValue        ( fft_desc, DFTI_INPUT_STRIDES , cs);
    DftiSetValue        ( fft_desc, DFTI_OUTPUT_STRIDES, rs);
    DftiCommitDescriptor( fft_desc );
    DftiComputeBackward ( fft_desc, out_fft, out2 );

    // Printing the zero padded 3D convolved result.
    for( long long i = 0; i < (long long)N*N*N; i++ )
        printf( out2, N*N*N );
    
    /* I don't know how to take out the zero padded results and 
       save the actual result in the variable named "out" */

    DftiFreeDescriptor  ( &fft_desc );

    delete[] in_fft;
    delete[] ker_fft;
    delete[] out2;
}

int max(int a, int b, int c)
{
     int m = a;
     (m < b) && (m = b); //these are not conditional statements.
     (m < c) && (m = c); //these are just boolean expressions.
     return m;
}

 

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